Reversible encephalitis-like episodes in fragile X-associated tremor/ataxia syndrome: a case report.

BACKGROUND: Fragile X-associated tremor/ataxia syndrome (FXTAS) is a neurodegenerative disorder caused by CGG repeat expansion of FMR1 gene. Both FXTAS and neuronal intranuclear inclusion disease (NIID) belong to polyglycine diseases and present similar clinical, radiological, and pathological features, making it difficult to distinguish these diseases. Reversible encephalitis-like attacks are often observed in NIID. It is unclear whether they are presented in FXTAS and can be used for differential diagnosis of NIID and FXTAS. CASE PRESENTATION: A 63-year-old Chinese male with late-onset gait disturbance, cognitive decline, and reversible attacks of fever, consciousness impairment, dizziness, vomiting, and urinary incontinence underwent neurological assessment and examinations, including laboratory tests, electroencephalogram test, imaging, skin biopsy, and genetic test. Brain MRI showed T2 hyperintensities in middle cerebellar peduncle and cerebrum, in addition to cerebellar atrophy and DWI hyperintensities along the corticomedullary junction. Lesions in the brainstem were observed. Skin biopsy showed p62-positive intranuclear inclusions. The possibilities of hypoglycemia, lactic acidosis, epileptic seizures, and cerebrovascular attacks were excluded. Genetic analysis revealed CGG repeat expansion in FMR1 gene, and the number of repeats was 111. The patient was finally diagnosed as FXTAS. He received supportive treatment as well as symptomatic treatment during hospitalization. His encephalitic symptoms were completely relieved within one week. CONCLUSIONS: This is a detailed report of a case of FXTAS with reversible encephalitis-like episodes. This report provides new information for the possible and rare features of FXTAS, highlighting that encephalitis-like episodes are common in polyglycine diseases and unable to be used for differential diagnosis.

Tau- and α-synuclein-targeted gold nanoparticles: applications, opportunities, and future outlooks in the diagnosis and therapy of neurodegenerative diseases.

The use of nanomaterials in medicine offers multiple opportunities to address neurodegenerative disorders such as Alzheimer's and Parkinson's disease. These diseases are a significant burden for society and the health system, affecting millions of people worldwide without sensitive and selective diagnostic methodologies or effective treatments to stop their progression. In this sense, the use of gold nanoparticles is a promising tool due to their unique properties at the nanometric level. They can be functionalized with specific molecules to selectively target pathological proteins such as Tau and α-synuclein for Alzheimer's and Parkinson's disease, respectively. Additionally, these proteins are used as diagnostic biomarkers, wherein gold nanoparticles play a key role in enhancing their signal, even at the low concentrations present in biological samples such as blood or cerebrospinal fluid, thus enabling an early and accurate diagnosis. On the other hand, gold nanoparticles act as drug delivery platforms, bringing therapeutic agents directly into the brain, improving treatment efficiency and precision, and reducing side effects in healthy tissues. However, despite the exciting potential of gold nanoparticles, it is crucial to address the challenges and issues associated with their use in the medical field before they can be widely applied in clinical settings. It is critical to ensure the safety and biocompatibility of these nanomaterials in the context of the central nervous system. Therefore, rigorous preclinical and clinical studies are needed to assess the efficacy and feasibility of these strategies in patients. Since there is scarce and sometimes contradictory literature about their use in this context, the main aim of this review is to discuss and analyze the current state-of-the-art of gold nanoparticles in relation to delivery, diagnosis, and therapy for Alzheimer's and Parkinson's disease, as well as recent research about their use in preclinical, clinical, and emerging research areas.

Amyloid detection in neurodegenerative diseases using MOFs.

Neurodegenerative diseases (amyloid diseases such as Alzheimer's and Parkinson's), stemming from protein misfolding and aggregation, encompass a spectrum of disorders with severe systemic implications. Timely detection is pivotal in managing these diseases owing to their significant impact on organ function and high mortality rates. The diverse array of amyloid disorders, spanning localized and systemic manifestations, underscores the complexity of these conditions and highlights the need for advanced detection methods. Traditional approaches have focused on identifying biomarkers using imaging techniques (PET and MRI) or invasive procedures. However, recent efforts have focused on the use of metal-organic frameworks (MOFs), a versatile class of materials known for their unique properties, in revolutionizing amyloid disease detection. The high porosity, customizable structures, and biocompatibility of MOFs enable their integration with biomolecules, laying the groundwork for highly sensitive and specific biosensors. These sensors have been employed using electrochemical and photophysical techniques that target amyloid species under neurodegenerative conditions. The adaptability of MOFs allows for the precise detection and quantification of amyloid proteins, offering potential advancements in early diagnosis and disease management. This review article delves into how MOFs contribute to detecting amyloid diseases by categorizing their uses based on different sensing methods, such as electrochemical (EC), electrochemiluminescence (ECL), fluorescence, Förster resonance energy transfer (FRET), up-conversion luminescence resonance energy transfer (ULRET), and photoelectrochemical (PEC) sensing. The drawbacks of MOF biosensors and the challenges encountered in the field are also briefly explored from our perspective.

Psychosis in Neurodegenerative Dementias: A Systematic Comparative Review.

Background: Psychosis, characterized by delusions and/or hallucinations, is frequently observed during the progression of Alzheimer's disease (AD) and other neurodegenerative dementias (ND) (i.e., dementia with Lewy bodies (DLB), and frontotemporal dementia (FTD)) and cause diagnostic and management difficulties. Objective: This review aims at presenting a concise and up-to-date overview of psychotic symptoms that occur in patients with ND with a comparative approach. Methods: A systematic review was conducted following the PRISMA guidelines. 98 original studies investigating psychosis phenotypes in neurodegenerative dementias were identified (40 cohort studies, 57 case reports). Results: Psychosis is a frequently observed phenomenon during the course of ND, with reported prevalence ranging from 22.5% to 54.1% in AD, 55.9% to 73.9% in DLB, and 18% to 42% in FTD. Throughout all stages of these diseases, noticeable patterns emerge depending on their underlying causes. Misidentification delusions (16.6-78.3%) and visual hallucinations (50-69.6%) are frequently observed in DLB, while paranoid ideas and somatic preoccupations seem to be particularly common in AD and FTD, (respectively 9.1-60.3% and 3.10-41.5%). Limited data were found regarding psychosis in the early stages of these disorders. Conclusions: Literature data suggest that different ND are associated with noticeable variations in psychotic phenotypes, reflecting disease-specific tendencies. Further studies focusing on the early stages of these disorders are necessary to enhance our understanding of early psychotic manifestations associated with ND and help in differential diagnosis issues.

Biomarkers for Managing Neurodegenerative Diseases.

Neurological disorders are the leading cause of cognitive and physical disability worldwide, affecting 15% of the global population. Due to the demographics of aging, the prevalence of neurological disorders, including neurodegenerative diseases, will double over the next two decades. Unfortunately, while available therapies provide symptomatic relief for cognitive and motor impairment, there is an urgent unmet need to develop disease-modifying therapies that slow the rate of pathological progression. In that context, biomarkers could identify at-risk and prodromal patients, monitor disease progression, track responses to therapy, and parse the causality of molecular events to identify novel targets for further clinical investigation. Thus, identifying biomarkers that discriminate between diseases and reflect specific stages of pathology would catalyze the discovery and development of therapeutic targets. This review will describe the prevalence, known mechanisms, ongoing or recently concluded therapeutic clinical trials, and biomarkers of three of the most prevalent neurodegenerative diseases, including Alzheimer's disease (AD), amyotrophic lateral sclerosis (ALS), and Parkinson's disease (PD).

Diagnosing aceruloplasminemia: navigating through red herrings.

A 58-year-old female was found to have hyperferritinemia (Serum ferritin:1683 ng/mL) during work-up for mild normocytic anemia. Transferrin saturation(TSAT) was low-normal. Magnetic resonance imaging (MRI) abdomen showed evidence of hepatic iron deposition. Liver biopsy showed 4 + hepatic iron deposition without any evidence of steatosis or fibrosis. Quantitative liver iron was elevated at 348.3 µmol/g dry liver weight [Reference range(RR): 3-33 µmol/g dry liver weight]. She was presumptively diagnosed with tissue iron overload, cause uncertain. A diagnosis of ferroportin disease (FD) was considered, but the pattern of iron distribution in the liver, mainly within the hepatic parenchyma (rather than in the hepatic Kupffer cells seen in FD), and the presence of anemia (uncommon in FD) made this less likely. She was treated with intermittent phlebotomy for over a decade with poor tolerance due to worsening normocytic to microcytic anemia. A trial of deferasirox was done but it was discontinued after a month due to significant side effects. During the course of treatment, her ferritin level decreased. Over the past 1.5 years, she developed progressively worsening neurocognitive decline. MRI brain showed areas of susceptibility involving basal ganglia, midbrain and cerebellum raising suspicion for metabolic deposition disease. Neuroimaging findings led to testing for serum copper and ceruloplasmin levels which were both found to be severely low. Low serum copper, ceruloplasmin levels and neuroimaging findings led us to consider Wilson disease however prior liver biopsy showing elevated hepatic iron rather than hepatic copper excluded the diagnosis of Wilson disease. After shared decision making, ceruloplasmin gene analysis was not pursued due to patient's preference and prohibitive cost of testing. The diagnosis of aceruloplasminemia was ultimately made. The biochemical triad of hyperferritinemia, low-normal TSAT and microcytic anemia should raise the possibility of aceruloplasminemia. Since neurological manifestations are rare in most inherited iron overload syndromes, neurological symptoms in a patient with tissue iron overload should prompt consideration of aceruloplasminemia as a differential diagnosis.

Molecular Biomarkers of Neurodegenerative Disorders: A Practical Guide to Their Appropriate Use and Interpretation in Clinical Practice.

Neurodegenerative disorders (NDs) represent a group of different diseases characterized by the progressive degeneration and death of the nervous system's cells. The diagnosis is challenging, especially in the early stages, due to no specific clinical signs and symptoms. In this context, laboratory medicine could support clinicians in detecting and differentiating NDs. Indeed, biomarkers could indicate the pathological mechanisms underpinning NDs. The ideal biofluid for detecting the biomarkers of NDs is cerebrospinal fluid (CSF), which has limitations, hampering its widespread use in clinical practice. However, intensive efforts are underway to introduce high-sensitivity analytical methods to detect ND biomarkers in alternative nonivasive biofluid, such as blood or saliva. This study presents an overview of the ND molecular biomarkers currently used in clinical practice. For some diseases, such as Alzheimer's disease or multiple sclerosis, biomarkers are well established and recommended by guidelines. However, for most NDs, intensive research is ongoing to identify reliable and specific biomarkers, and no consensus has yet been achieved.

New knowledge on anti-IgLON5 disease.

PURPOSE OF REVIEW: Anti-IgLON5 disease is characterized by a distinctive sleep disorder, associated with a heterogeneous spectrum of neurological symptoms. Initial autopsies showed a novel neuronal tauopathy predominantly located in the tegmentum of the brainstem. Recently, new diagnostic red flags, biomarkers predictors of response to immunotherapy, and novel insights into the autoimmune pathogenesis of the disease have been reported. RECENT FINDINGS: Patients with diagnosis of neurodegenerative dementia, progressive supranuclear palsy (PSP) or with motor-neuron disease (MND)-like syndrome have been reported to have IgLON5 antibodies, which are the hallmark of anti-IgLON5 disease. Second, low levels of neurofilament light chain in serum and cerebrospinal fluid of patients at disease onset could be a predictor of immunotherapy response. Recent neuropathological studies indicate that the neuronal tau deposits occur late in the course of the disease. Moreover, IgLON5 antibodies induce cytoskeletal changes in cultured hippocampal neurons suggesting that the tauopathy could be secondary of the IgLON5 antibody effects. SUMMARY: Anti-IgLON5 disease can mimic and should be considered in atypical presentations of MND, neurodegenerative dementia and PSP. Neurofilament light chain levels seem promising biomarker for disease prognosis. Finally, the neuropathological and in vitro experimental studies strengthen the autoimmune hypothesis of the disease.

Neuronal intranuclear inclusion disease misdiagnosed as Parkinson's disease: a case report.

Neuronal intranuclear inclusion disease (NIID) is a rare progressive neurodegenerative disease that mainly manifests as dementia, muscle weakness, sensory disturbances, and autonomic nervous dysfunction. Herein, we report a 68-year-old Chinese woman who was hospitalized because of resting tremor and bradykinesia that had been present for 7 years. Five years prior, bradykinesia and hypermyotonia had become apparent. She had urinary incontinence and rapid eye movement sleep behavior disorder. She was diagnosed with Parkinson's disease (PD) and received levodopa and pramipexole, which relieved her motor symptoms. During hospitalization, diffusion-weighted imaging revealed a high-intensity signal along the cortical medullary junction. Moreover, a skin biopsy revealed the presence of intranuclear inclusions in adipocytes, fibroblasts, and sweat gland cells. NIID was diagnosed by testing the Notch 2 N-terminal-like C (NOTCH2NLC) gene. We report this case to remind doctors to consider NIID when diagnosing patients with symptoms indicative of Parkinson's disease. Moreover, we note that further research is needed on the mechanism by which levodopa is effective for NIID.

Machine Learning and Digital Biomarkers Can Detect Early Stages of Neurodegenerative Diseases.

Neurodegenerative diseases (NDs) such as Alzheimer's Disease (AD) and Parkinson's Disease (PD) are devastating conditions that can develop without noticeable symptoms, causing irreversible damage to neurons before any signs become clinically evident. NDs are a major cause of disability and mortality worldwide. Currently, there are no cures or treatments to halt their progression. Therefore, the development of early detection methods is urgently needed to delay neuronal loss as soon as possible. Despite advancements in Medtech, the early diagnosis of NDs remains a challenge at the intersection of medical, IT, and regulatory fields. Thus, this review explores "digital biomarkers" (tools designed for remote neurocognitive data collection and AI analysis) as a potential solution. The review summarizes that recent studies combining AI with digital biomarkers suggest the possibility of identifying pre-symptomatic indicators of NDs. For instance, research utilizing convolutional neural networks for eye tracking has achieved significant diagnostic accuracies. ROC-AUC scores reached up to 0.88, indicating high model performance in differentiating between PD patients and healthy controls. Similarly, advancements in facial expression analysis through tools have demonstrated significant potential in detecting emotional changes in ND patients, with some models reaching an accuracy of 0.89 and a precision of 0.85. This review follows a structured approach to article selection, starting with a comprehensive database search and culminating in a rigorous quality assessment and meaning for NDs of the different methods. The process is visualized in 10 tables with 54 parameters describing different approaches and their consequences for understanding various mechanisms in ND changes. However, these methods also face challenges related to data accuracy and privacy concerns. To address these issues, this review proposes strategies that emphasize the need for rigorous validation and rapid integration into clinical practice. Such integration could transform ND diagnostics, making early detection tools more cost-effective and globally accessible. In conclusion, this review underscores the urgent need to incorporate validated digital health tools into mainstream medical practice. This integration could indicate a new era in the early diagnosis of neurodegenerative diseases, potentially altering the trajectory of these conditions for millions worldwide. Thus, by highlighting specific and statistically significant findings, this review demonstrates the current progress in this field and the potential impact of these advancements on the global management of NDs.

Clinical advances in analytical profiling of signature lipids: implications for severe non-communicable and neurodegenerative diseases.

BACKGROUND: Lipids play key roles in numerous biological processes, including energy storage, cell membrane structure, signaling, immune responses, and homeostasis, making lipidomics a vital branch of metabolomics that analyzes and characterizes a wide range of lipid classes. Addressing the complex etiology, age-related risk, progression, inflammation, and research overlap in conditions like Alzheimer's Disease, Parkinson's Disease, Cardiovascular Diseases, and Cancer poses significant challenges in the quest for effective therapeutic targets, improved diagnostic markers, and advanced treatments. Mass spectrometry is an indispensable tool in clinical lipidomics, delivering quantitative and structural lipid data, and its integration with technologies like Liquid Chromatography (LC), Magnetic Resonance Imaging (MRI), and few emerging Matrix-Assisted Laser Desorption Ionization- Imaging Mass Spectrometry (MALDI-IMS) along with its incorporation into Tissue Microarray (TMA) represents current advances. These innovations enhance lipidomics assessment, bolster accuracy, and offer insights into lipid subcellular localization, dynamics, and functional roles in disease contexts. AIM OF THE REVIEW: The review article summarizes recent advancements in lipidomic methodologies from 2019 to 2023 for diagnosing major neurodegenerative diseases, Alzheimer's and Parkinson's, serious non-communicable cardiovascular diseases and cancer, emphasizing the role of lipid level variations, and highlighting the potential of lipidomics data integration with genomics and proteomics to improve disease understanding and innovative prognostic, diagnostic and therapeutic strategies. KEY SCIENTIFIC CONCEPTS OF REVIEW: Clinical lipidomic studies are a promising approach to track and analyze lipid profiles, revealing their crucial roles in various diseases. This lipid-focused research provides insights into disease mechanisms, biomarker identification, and potential therapeutic targets, advancing our understanding and management of conditions such as Alzheimer's Disease, Parkinson's Disease, Cardiovascular Diseases, and specific cancers.

Identification of clinical disease trajectories in neurodegenerative disorders with natural language processing.

Neurodegenerative disorders exhibit considerable clinical heterogeneity and are frequently misdiagnosed. This heterogeneity is often neglected and difficult to study. Therefore, innovative data-driven approaches utilizing substantial autopsy cohorts are needed to address this complexity and improve diagnosis, prognosis and fundamental research. We present clinical disease trajectories from 3,042 Netherlands Brain Bank donors, encompassing 84 neuropsychiatric signs and symptoms identified through natural language processing. This unique resource provides valuable new insights into neurodegenerative disorder symptomatology. To illustrate, we identified signs and symptoms that differed between frequently misdiagnosed disorders. In addition, we performed predictive modeling and identified clinical subtypes of various brain disorders, indicative of neural substructures being differently affected. Finally, integrating clinical diagnosis information revealed a substantial proportion of inaccurately diagnosed donors that masquerade as another disorder. The unique datasets allow researchers to study the clinical manifestation of signs and symptoms across neurodegenerative disorders, and identify associated molecular and cellular features.

Highly sensitive detection of the neurodegenerative biomarker Tau by using the concentration effect of the pyro-electrohydrodynamic jetting.

It is largely documented that neurodegenerative diseases can be effectively treated only if early diagnosed. In this context, the structural changes of some biomolecules such as Tau, seem to play a key role in neurodegeneration mechanism becoming eligible targets for an early diagnosis. Post-translational modifications are responsible to drive the Tau protein towards a transition phase from a native disorder conformation into a preaggregation state, which then straight recruits the final fibrillization process. Here, we show for the first time the detection of pre-aggregated Tau in artificial urine at femto-molar level, through the concentration effect of the pyro-electrohydrodynamic jet (p-jet) technique. An excellent linear calibration curve is demonstrated at the femto-molar level with a limit of detection (LOD) of 130 fM. Moreover, for the first time we show here the structure stability of the protein after p-jet application through a deep spectroscopic investigation. Thanks to the small volumes required and the relatively compact and cost-effective characteristics, this technique represents an innovative breakthrough in monitoring the early stage associated to neurodegeneration syndromes in different scenarios of point of care (POC) and such as for example in long-term human space exploration missions.

Assessing Cognitive Workload in Motor Decision-Making through Functional Connectivity Analysis: Towards Early Detection and Monitoring of Neurodegenerative Diseases.

Neurodegenerative diseases (NDs), such as Alzheimer's, Parkinson's, amyotrophic lateral sclerosis, and frontotemporal dementia, among others, are increasingly prevalent in the global population. The clinical diagnosis of these NDs is based on the detection and characterization of motor and non-motor symptoms. However, when these diagnoses are made, the subjects are often in advanced stages where neuromuscular alterations are frequently irreversible. In this context, we propose a methodology to evaluate the cognitive workload (CWL) of motor tasks involving decision-making processes. CWL is a concept widely used to address the balance between task demand and the subject's available resources to complete that task. In this study, multiple models for motor planning during a motor decision-making task were developed by recording EEG and EMG signals in n=17 healthy volunteers (9 males, 8 females, age 28.66±8.8 years). In the proposed test, volunteers have to make decisions about which hand should be moved based on the onset of a visual stimulus. We computed functional connectivity between the cortex and muscles, as well as among muscles using both corticomuscular and intermuscular coherence. Despite three models being generated, just one of them had strong performance. The results showed two types of motor decision-making processes depending on the hand to move. Moreover, the central processing of decision-making for the left hand movement can be accurately estimated using behavioral measures such as planning time combined with peripheral recordings like EMG signals. The models provided in this study could be considered as a methodological foundation to detect neuromuscular alterations in asymptomatic patients, as well as to monitor the process of a degenerative disease.

Endo-lysosomal dysfunction in neurodegenerative diseases: opinion on current progress and future direction in the use of exosomes as biomarkers.

Over the past two decades, increased research has highlighted the connection between endosomal trafficking defects and neurodegeneration. The endo-lysosomal network is an important, complex cellular system specialized in the transport of proteins, lipids, and other metabolites, essential for cell homeostasis. Disruption of this pathway is linked to a wide range of neurodegenerative diseases, including Alzheimer's disease, Parkinson's disease, amyotrophic lateral sclerosis, Huntington's disease and frontotemporal dementia. Furthermore, there is strong evidence that defects in this pathway create opportunities for diagnostic and therapeutic intervention. In this Opinion piece, we concisely address the role of endo-lysosomal dysfunction in five neurodegenerative diseases and discuss how future research can investigate this intracellular pathway, including extracellular vesicles with a specific focus on exosomes for the identification of novel disease biomarkers. This article is part of a discussion meeting issue 'Understanding the endo-lysosomal network in neurodegeneration'.

The potential roles of salivary biomarkers in neurodegenerative diseases.

Current research efforts on neurodegenerative diseases are focused on identifying novel and reliable biomarkers for early diagnosis and insight into disease progression. Salivary analysis is gaining increasing interest as a promising source of biomarkers and matrices for measuring neurodegenerative diseases. Saliva collection offers multiple advantages over the currently detected biofluids as it is easily accessible, non-invasive, and repeatable, allowing early diagnosis and timely treatment of the diseases. Here, we review the existing findings on salivary biomarkers and address the potential value in diagnosing neurodegenerative diseases, such as Alzheimer's disease, Parkinson's disease, Huntington's disease and Amyotrophic lateral sclerosis. Based on the available research, ß-amyloid, tau protein, α-synuclein, DJ-1, Huntington protein in saliva profiles display reliability and validity as the biomarkers of neurodegenerative diseases.

Proteomics: Unraveling the Cross Talk Between Innate Immunity and Disease Pathophysiology, Diagnostics, and Treatment Options.

Inflammation is crucial in diseases, and proteins play a key role in the interplay between innate immunity and pathology. This review explores how proteomics helps understanding this relationship, focusing on diagnosis and treatment. We explore the dynamic innate response and the significance of proteomic techniques in deciphering the complex network of proteins involved in prevalent diseases, including infections, cancer, autoimmune and neurodegenerative disorders. Proteomics identifies key proteins in host-pathogen interactions, shedding light on infection mechanisms and inflammation. These discoveries hold promise for diagnostic tools, therapies, and vaccines. In cancer research, proteomics reveals innate signatures associated with tumor development, immune evasion, and therapeutic response. Additionally, proteomic analysis has unveiled autoantigens and dysregulation of the innate immune system in autoimmunity, offering opportunities for early diagnosis, disease monitoring, and new therapeutic targets. Moreover, proteomic analysis has identified altered protein expression patterns in neurodegenerative diseases like Alzheimer's and Parkinson's, providing insights into potential therapeutic strategies. Proteomics of the innate immune system provides a comprehensive understanding of disease mechanisms, identifies biomarkers, and enables effective interventions in various diseases. Despite still in its early stages, this approach holds great promise to revolutionize innate immunity research and significantly improve patient outcomes across a wide range of diseases.